Berlin
Data for Berlin
Data for the city of Berlin are periodically reported from the Landesamt für Gesundheit und Soziales of the Berlin Council.
import os,sys
sys.path.insert(0, os.path.normpath(os.path.join(os.path.abspath(''), '../../Code')))
from hedera_covid import DataHandlerBerlin, smooth_data
# for plotly
from plotly.offline import iplot
from plotly.offline import init_notebook_mode, plot
from IPython.core.display import display, HTML
import plotly as py
import plotly.tools as tls
import datetime
import numpy as np
import pandas as pd
# load data
berlin = DataHandlerBerlin()
# intensive care
berlin_h = pd.read_excel('../../DE-Data/intensive-care-data.xlsx',sheet_name = 'berlin')
germany_h = pd.read_excel('../../DE-Data/intensive-care-data.xlsx',sheet_name = 'germany')
bayern_h = pd.read_excel('../../DE-Data/intensive-care-data.xlsx',sheet_name = 'bayern')
import plotly.graph_objects as go
init_notebook_mode(connected=True)
fig = go.Figure()
N = len(berlin.data['dates'])
fig.add_trace(go.Bar(
x=berlin.data['dates'],
y=smooth_data(berlin.data['confirmed'],7),
name='Reported Cases (Total = ' + str(berlin.data['confirmed'][N-1]) + ')'
))
fig.add_trace(go.Bar(
x=berlin.data['dates'],
y=smooth_data(berlin.data['deaths'],7),
name='Reported Deaths (Total = ' + str(berlin.data['deaths'][N-1]) + ')'
))
fig.add_trace(go.Scatter(
x=berlin.data['dates'],
y=smooth_data(berlin.data['stationary'],7),
name='In Hospital (Total = ' + str(berlin.data['stationary'][N-1]) + ')'
))
fig.add_trace(go.Scatter(
x=berlin.data['dates'],
y=smooth_data(berlin.data['intensive'],7),
name='Intensive Care (Total = ' + str(berlin.data['intensive'][N-1]) + ')'
))
fig.update_layout(xaxis_tickangle=-90)
plot(fig, filename = 'figure.html')
display(HTML('figure.html'))
import plotly.graph_objects as go
init_notebook_mode(connected=True)
fig = go.Figure()
fig.add_trace(go.Bar(
x=berlin.data['dates'],
y=berlin.data['confirmed_daily'],
name='Daily Reported Cases (Total = ' + str(berlin.data['confirmed'][N-1]) + ')',
marker = {'color': "#117A65"}
))
n_smooth = 7
fig.add_trace(go.Scatter(
x=berlin.data['dates'],
y=smooth_data(berlin.data['confirmed_daily'],n=n_smooth),
name='Averaged over ' + str(n_smooth) + ' days',
marker = {'color': "#48C9B0"}
))
fig.add_trace(go.Bar(
x=berlin.data['dates'],
y=berlin.data['deaths_daily'],
name='Daily Reported Deaths (Total = ' + str(berlin.data['deaths'][N-1]) + ')',
marker = {'color':'#F7DC6F'}
))
n_smooth = 3
fig.add_trace(go.Scatter(
x=berlin.data['dates'],
y=smooth_data(berlin.data['deaths_daily'],n=n_smooth),
name='Averaged over ' + str(n_smooth) + ' days',
marker = {'color': "#EB984E"}
))
fig.update_layout(xaxis_tickangle=-90)
fig.update_layout(legend=dict(x=0.1, y=1.2),legend_orientation="h",font_size=10)
plot(fig, filename = 'figure.html')
display(HTML('figure.html'))
import plotly.graph_objects as go
init_notebook_mode(connected=True)
fig = go.Figure()
fig.add_trace(go.Bar(
x=germany_h['Date'],
y=germany_h['Percentage'],
name='Germany',
marker = {'color': "#F7DC6F"}
))
fig.add_trace(go.Bar(
x=berlin_h['Date'],
y=berlin_h['Percentage'],
name='Berlin',
marker = {'color': "#117A65"}
))
fig.add_trace(go.Bar(
x=bayern_h['Date'],
y=bayern_h['Percentage'],
name='Bayern',
marker = {'color': "#48C9B0"}
))
fig.update_layout(xaxis_tickangle=-90)
fig.update_layout(title='Percentage of intensive beds free',legend=dict(x=0.1, y=-.1),
legend_orientation="h",font_size=10)
#fig.show()
plot(fig, filename = 'figure.html')
display(HTML('figure.html'))
g=10
from IPython.display import display, Markdown
N = len(germany_h['Reporting'])
g= germany_h['Reporting'][N-1]
d = germany_h['Date'][N-1]
display(Markdown(f'**Note** The graphics take into account only the reporting entities ({g} on {d})'))